Overview

Dataset statistics

Number of variables5
Number of observations39
Missing cells12
Missing cells (%)6.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.7 KiB
Average record size in memory44.4 B

Variable types

Numeric1
Text4

Dataset

Description인천광역시 서구 고물상 현황에 관한 데이터입니다. 상호, 주소, 취급품목, 전화번호 등의 항목을 제공하고 있습니다.
Author인천광역시 서구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15121224&srcSe=7661IVAWM27C61E190

Alerts

전화번호 has 12 (30.8%) missing valuesMissing
연번 has unique valuesUnique
상호 has unique valuesUnique
주소 has unique valuesUnique

Reproduction

Analysis started2024-01-28 08:49:24.327218
Analysis finished2024-01-28 08:49:24.836587
Duration0.51 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct39
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20
Minimum1
Maximum39
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size483.0 B
2024-01-28T17:49:24.895504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.9
Q110.5
median20
Q329.5
95-th percentile37.1
Maximum39
Range38
Interquartile range (IQR)19

Descriptive statistics

Standard deviation11.401754
Coefficient of variation (CV)0.57008771
Kurtosis-1.2
Mean20
Median Absolute Deviation (MAD)10
Skewness0
Sum780
Variance130
MonotonicityStrictly increasing
2024-01-28T17:49:25.014810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
1 1
 
2.6%
2 1
 
2.6%
23 1
 
2.6%
24 1
 
2.6%
25 1
 
2.6%
26 1
 
2.6%
27 1
 
2.6%
28 1
 
2.6%
29 1
 
2.6%
30 1
 
2.6%
Other values (29) 29
74.4%
ValueCountFrequency (%)
1 1
2.6%
2 1
2.6%
3 1
2.6%
4 1
2.6%
5 1
2.6%
6 1
2.6%
7 1
2.6%
8 1
2.6%
9 1
2.6%
10 1
2.6%
ValueCountFrequency (%)
39 1
2.6%
38 1
2.6%
37 1
2.6%
36 1
2.6%
35 1
2.6%
34 1
2.6%
33 1
2.6%
32 1
2.6%
31 1
2.6%
30 1
2.6%

상호
Text

UNIQUE 

Distinct39
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size444.0 B
2024-01-28T17:49:25.214704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length6.2820513
Min length3

Characters and Unicode

Total characters245
Distinct characters81
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique39 ?
Unique (%)100.0%

Sample

1st row㈜해천자원
2nd row㈜유진스틸
3rd row㈜장원금속
4th row한신에스앤드㈜
5th row㈜신성스틸
ValueCountFrequency (%)
㈜해천자원 1
 
2.3%
지구이앤에스㈜지점 1
 
2.3%
조양인더스트리㈜ 1
 
2.3%
㈜경인펄프 1
 
2.3%
경인에코텍㈜ 1
 
2.3%
서인천지점 1
 
2.3%
㈜중부자원 1
 
2.3%
현일산업㈜ 1
 
2.3%
오케이환경 1
 
2.3%
㈜도나스틸 1
 
2.3%
Other values (33) 33
76.7%
2024-01-28T17:49:25.556847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 32
 
13.1%
인 12
 
4.9%
원 11
 
4.5%
스 11
 
4.5%
이 9
 
3.7%
자 8
 
3.3%
경 8
 
3.3%
지 7
 
2.9%
에 6
 
2.4%
점 5
 
2.0%
Other values (71) 136
55.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 207
84.5%
Other Symbol 32
 
13.1%
Space Separator 4
 
1.6%
Close Punctuation 1
 
0.4%
Open Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 12
 
5.8%
원 11
 
5.3%
스 11
 
5.3%
이 9
 
4.3%
자 8
 
3.9%
경 8
 
3.9%
지 7
 
3.4%
에 6
 
2.9%
점 5
 
2.4%
산 5
 
2.4%
Other values (67) 125
60.4%
Other Symbol
ValueCountFrequency (%)
㈜ 32
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 239
97.6%
Common 6
 
2.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 32
 
13.4%
인 12
 
5.0%
원 11
 
4.6%
스 11
 
4.6%
이 9
 
3.8%
자 8
 
3.3%
경 8
 
3.3%
지 7
 
2.9%
에 6
 
2.5%
점 5
 
2.1%
Other values (68) 130
54.4%
Common
ValueCountFrequency (%)
4
66.7%
) 1
 
16.7%
( 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 207
84.5%
None 32
 
13.1%
ASCII 6
 
2.4%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 32
100.0%
Hangul
ValueCountFrequency (%)
인 12
 
5.8%
원 11
 
5.3%
스 11
 
5.3%
이 9
 
4.3%
자 8
 
3.9%
경 8
 
3.9%
지 7
 
3.4%
에 6
 
2.9%
점 5
 
2.4%
산 5
 
2.4%
Other values (67) 125
60.4%
ASCII
ValueCountFrequency (%)
4
66.7%
) 1
 
16.7%
( 1
 
16.7%

주소
Text

UNIQUE 

Distinct39
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size444.0 B
2024-01-28T17:49:25.779625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length32
Mean length21.589744
Min length15

Characters and Unicode

Total characters842
Distinct characters69
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique39 ?
Unique (%)100.0%

Sample

1st row인천 서구 보도진로 90(가좌동)
2nd row인천 서구 보듬1로 44(오류동)
3rd row인천 서구 마전동 632-6
4th row인천 서구 오류동 1612-9(검단일반산업단지 2-4블럭)
5th row인천 서구 경서동 350-20
ValueCountFrequency (%)
인천 39
22.7%
서구 39
22.7%
오류동 11
 
6.4%
원당대로 4
 
2.3%
검단로188번길 2
 
1.2%
가좌동 2
 
1.2%
마전동 2
 
1.2%
38 2
 
1.2%
보도진로 2
 
1.2%
외1필지 1
 
0.6%
Other values (68) 68
39.5%
2024-01-28T17:49:26.486087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
133
 
15.8%
서 41
 
4.9%
인 40
 
4.8%
천 40
 
4.8%
구 39
 
4.6%
동 39
 
4.6%
3 38
 
4.5%
4 37
 
4.4%
1 33
 
3.9%
- 31
 
3.7%
Other values (59) 371
44.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 401
47.6%
Decimal Number 231
27.4%
Space Separator 133
 
15.8%
Dash Punctuation 31
 
3.7%
Open Punctuation 20
 
2.4%
Close Punctuation 20
 
2.4%
Other Punctuation 6
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 41
 
10.2%
인 40
 
10.0%
천 40
 
10.0%
구 39
 
9.7%
동 39
 
9.7%
로 21
 
5.2%
류 19
 
4.7%
오 19
 
4.7%
길 16
 
4.0%
번 13
 
3.2%
Other values (44) 114
28.4%
Decimal Number
ValueCountFrequency (%)
3 38
16.5%
4 37
16.0%
1 33
14.3%
2 27
11.7%
6 22
9.5%
7 20
8.7%
8 16
6.9%
9 16
6.9%
0 14
 
6.1%
5 8
 
3.5%
Space Separator
ValueCountFrequency (%)
133
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 31
100.0%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 441
52.4%
Hangul 401
47.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 41
 
10.2%
인 40
 
10.0%
천 40
 
10.0%
구 39
 
9.7%
동 39
 
9.7%
로 21
 
5.2%
류 19
 
4.7%
오 19
 
4.7%
길 16
 
4.0%
번 13
 
3.2%
Other values (44) 114
28.4%
Common
ValueCountFrequency (%)
133
30.2%
3 38
 
8.6%
4 37
 
8.4%
1 33
 
7.5%
- 31
 
7.0%
2 27
 
6.1%
6 22
 
5.0%
( 20
 
4.5%
) 20
 
4.5%
7 20
 
4.5%
Other values (5) 60
13.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 441
52.4%
Hangul 401
47.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
133
30.2%
3 38
 
8.6%
4 37
 
8.4%
1 33
 
7.5%
- 31
 
7.0%
2 27
 
6.1%
6 22
 
5.0%
( 20
 
4.5%
) 20
 
4.5%
7 20
 
4.5%
Other values (5) 60
13.6%
Hangul
ValueCountFrequency (%)
서 41
 
10.2%
인 40
 
10.0%
천 40
 
10.0%
구 39
 
9.7%
동 39
 
9.7%
로 21
 
5.2%
류 19
 
4.7%
오 19
 
4.7%
길 16
 
4.0%
번 13
 
3.2%
Other values (44) 114
28.4%

취급품목
Text

Distinct29
Distinct (%)74.4%
Missing0
Missing (%)0.0%
Memory size444.0 B
2024-01-28T17:49:26.672196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length31
Mean length11.076923
Min length2

Characters and Unicode

Total characters432
Distinct characters45
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)61.5%

Sample

1st row폐지,고철,폐포장재(폐합성용기류, 금속캔, 유리병)
2nd row고철, 비철
3rd row고철(비철포함)
4th row고철
5th row폐포장재(폐금속캔)
ValueCountFrequency (%)
고철 14
16.3%
폐지 10
 
11.6%
폐의류 8
 
9.3%
금속캔 7
 
8.1%
폐지류 5
 
5.8%
유리병 4
 
4.7%
포장재 3
 
3.5%
폐포장재 3
 
3.5%
폐포장재(금속캔 2
 
2.3%
폐합성수지 2
 
2.3%
Other values (25) 28
32.6%
2024-01-28T17:49:26.994542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
폐 51
 
11.8%
48
 
11.1%
, 48
 
11.1%
지 28
 
6.5%
철 23
 
5.3%
고 20
 
4.6%
재 18
 
4.2%
류 17
 
3.9%
포 16
 
3.7%
의 13
 
3.0%
Other values (35) 150
34.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 320
74.1%
Space Separator 48
 
11.1%
Other Punctuation 48
 
11.1%
Open Punctuation 8
 
1.9%
Close Punctuation 8
 
1.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
폐 51
15.9%
지 28
 
8.8%
철 23
 
7.2%
고 20
 
6.2%
재 18
 
5.6%
류 17
 
5.3%
포 16
 
5.0%
의 13
 
4.1%
장 13
 
4.1%
속 12
 
3.8%
Other values (31) 109
34.1%
Space Separator
ValueCountFrequency (%)
48
100.0%
Other Punctuation
ValueCountFrequency (%)
, 48
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 320
74.1%
Common 112
 
25.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
폐 51
15.9%
지 28
 
8.8%
철 23
 
7.2%
고 20
 
6.2%
재 18
 
5.6%
류 17
 
5.3%
포 16
 
5.0%
의 13
 
4.1%
장 13
 
4.1%
속 12
 
3.8%
Other values (31) 109
34.1%
Common
ValueCountFrequency (%)
48
42.9%
, 48
42.9%
( 8
 
7.1%
) 8
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 320
74.1%
ASCII 112
 
25.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
폐 51
15.9%
지 28
 
8.8%
철 23
 
7.2%
고 20
 
6.2%
재 18
 
5.6%
류 17
 
5.3%
포 16
 
5.0%
의 13
 
4.1%
장 13
 
4.1%
속 12
 
3.8%
Other values (31) 109
34.1%
ASCII
ValueCountFrequency (%)
48
42.9%
, 48
42.9%
( 8
 
7.1%
) 8
 
7.1%

전화번호
Text

MISSING 

Distinct27
Distinct (%)100.0%
Missing12
Missing (%)30.8%
Memory size444.0 B
2024-01-28T17:49:27.187725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.962963
Min length11

Characters and Unicode

Total characters323
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)100.0%

Sample

1st row032-423-6391
2nd row032-563-6447
3rd row032-561-1405
4th row032-590-9090
5th row032-576-4971
ValueCountFrequency (%)
032-423-6391 1
 
3.7%
032-565-7441 1
 
3.7%
032-263-000 1
 
3.7%
032-553-0744 1
 
3.7%
032-590-6900 1
 
3.7%
032-563-6755 1
 
3.7%
032-561-5900 1
 
3.7%
032-572-2676 1
 
3.7%
032-566-6020 1
 
3.7%
032-583-1188 1
 
3.7%
Other values (17) 17
63.0%
2024-01-28T17:49:27.511901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 54
16.7%
0 49
15.2%
5 43
13.3%
2 39
12.1%
3 37
11.5%
6 27
8.4%
7 18
 
5.6%
9 16
 
5.0%
1 16
 
5.0%
8 13
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 269
83.3%
Dash Punctuation 54
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 49
18.2%
5 43
16.0%
2 39
14.5%
3 37
13.8%
6 27
10.0%
7 18
 
6.7%
9 16
 
5.9%
1 16
 
5.9%
8 13
 
4.8%
4 11
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 54
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 323
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 54
16.7%
0 49
15.2%
5 43
13.3%
2 39
12.1%
3 37
11.5%
6 27
8.4%
7 18
 
5.6%
9 16
 
5.0%
1 16
 
5.0%
8 13
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 323
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 54
16.7%
0 49
15.2%
5 43
13.3%
2 39
12.1%
3 37
11.5%
6 27
8.4%
7 18
 
5.6%
9 16
 
5.0%
1 16
 
5.0%
8 13
 
4.0%

Interactions

2024-01-28T17:49:24.564251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T17:49:27.611951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번상호주소취급품목전화번호
연번1.0001.0001.0000.6381.000
상호1.0001.0001.0001.0001.000
주소1.0001.0001.0001.0001.000
취급품목0.6381.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.000

Missing values

2024-01-28T17:49:24.694399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T17:49:24.807080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

연번상호주소취급품목전화번호
01㈜해천자원인천 서구 보도진로 90(가좌동)폐지,고철,폐포장재(폐합성용기류, 금속캔, 유리병)032-423-6391
12㈜유진스틸인천 서구 보듬1로 44(오류동)고철, 비철032-563-6447
23㈜장원금속인천 서구 마전동 632-6고철(비철포함)032-561-1405
34한신에스앤드㈜인천 서구 오류동 1612-9(검단일반산업단지 2-4블럭)고철032-590-9090
45㈜신성스틸인천 서구 경서동 350-20폐포장재(폐금속캔)032-576-4971
56㈜빅스틸인천 서구 오류동 검단일반산업단지 10-21폐지032-578-7117
67경인리싸이클링㈜인천 서구 오류동 434-62고철032-565-1085
78㈜신의철강인천 서구 가좌동 178-260, 178-169폐지, 고철, 폐포장재032-582-9098
89남일상사인천 서구 오류동 434-373, 434-374, 434-376폐지, 고철032-567-2559
910동인자원㈜인천 서구 석남동 223-604폐지, 고철032-511-7791
연번상호주소취급품목전화번호
2930㈜성인 인천공장인천 서구 원당대로 262번길17(오류동 434-98)폐지류, 폐합성수지032-572-2676
3031㈜드림산업 인천지점인천 서구 검단로188번길 19 (오류동 421)고철<NA>
3132대한강업㈜인천 서구 사렴로65번길 19(경서동)폐지, 고철,유리병, 종이팩, 금속캔, 합성수지재질의 포장재 등, 폐전선, 폐가전제품(소형가전), 폐의류032-561-5900
3233태원자원인천 서구 길무로 191, 가동(오류동)폐지류<NA>
3334(주)리사이클한강인천 서구 금산로7번길 12금속캔, 고철, 비철금속, 폐지, 폐포장재(합성수지 재질의 포장재, 유리병), 폐의류032-563-6755
3435㈜부천리사이클링인천 서구 봉수대로1394번길32(왕길동)고철<NA>
3536한신에스앤드㈜지점인천 서구 중봉대로198번길 17(가좌동)폐포장재032-590-6900
3637부림인더스트리㈜인천 서구 두루물로96번길 26(오류동)폐지류, 고철032-553-0744
3738경인케미컬인천 서구 사월로 2 가동(백석동)폐지류032-569-3057
3839경인그린텍㈜ 지점인천 서구 두루물로 86(오류동)폐지류, 금속 및 고철캔류, 폐합성수지, 유리병, 폐의류<NA>